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This lecture by the instructor focuses on the application of machine learning techniques to monitor coral reefs in the Red Sea. The lecture covers the challenges faced by coral reefs due to climate change and human activities, highlighting the genetic resistance of Red Sea corals to heat stress. The instructor explains the process of 3D reconstruction of coral reefs using self-supervised learning for depth estimation and semantic segmentation. The goal is to create accurate 3D models of coral reefs for biodiversity assessment and genetic studies, emphasizing the importance of collaboration between machine learning experts and domain specialists in environmental conservation projects.